Growth Improvement with Adalimumab Treatment in Children with Moderately to Severely Active Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: Growth failure is common in children with Crohn's disease. The effect of adalimumab (ADA), a fully human antitumor necrosis factor antagonist, on height velocity in pediatric patients with baseline (BL) linear growth impairment in the IMAgINE 1 trial is presented. METHODS: This analysis included female and male patients with growth potential (bone age ≤13 and ≤14 yr, respectively), with BL Pediatric Crohn's disease Activity Index >30, and who failed or were intolerant to conventional therapy. Patients received open-label induction ADA at weeks 0 and 2 by body weight (≥40 kg, 160 and 80 mg and <40 kg, 80 and 40 mg). At week 4, patients were randomized to double-blind high (40 or 20 mg for ≥40 kg or <40 kg) or low dose (20 or 10 mg for ≥40 kg or <40 kg) every other week ADA to week 52. Height velocity z-score was summarized at BL, week 26, and week 52 by patients with BL growth impairment (z-score ≤-1.0) or normal growth (z-score >-1.0). RESULTS: ADA therapy significantly improved and normalized growth rate at weeks 26 and 52 in patients with BL growth impairment (median z-score, BL, -3.25; week 26, -0.34; and week 52, 0.21; P < 0.001 versus BL for both), but not in patients with normal growth. Growth improvement was significantly greater at week 26 in week 4 responders to induction therapy compared with nonresponders (median z-score 0.09 versus -2.92; P = 0.02). CONCLUSIONS: ADA treatment resulted in growth rate normalization as early as week 26 in children with moderately to severely active Crohn's disease and growth impairment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".